Hybrid Method In Revealing Facts Behind Texts: A Combination Of Text Mining And Qualitative Approach
Ujang Fahmi, Canggih Puspo Wibowo, Faturahman Yudanto · 2018
Social media has become one of the primary sources of data which available for policy analysts and policymakers.As the evidence, active Twitter users are sending 500 million tweets per day containing thoughts, opinions, pictures, and other information.Social media offers new challenges related to how the data is acquired and how to analyze it.Unfortunately, the state-of-the-art methods in text mining are still unable to interpret texts fully.Thus, in social media analysis, we can only make a conclusion based on the insight into an event.Therefore, we propose a hybrid method that combines text mining and qualitative methods for analyzing social media data.This research was composed based on a review of studies and experimental results on the data taken from the Twitter.The results show that both techniques can complement each other and give in-depth analysis of the data.Furthermore, the results can be employed to observe social media data in a faster, cheaper, and more precise way.More importantly, the results of this study serve as a basis for further development of a method to reveal the facts behind texts that obtained from social media.